Data SciencePhilosophy
I believe data science is not just about algorithms and statistics—it's about storytelling through numbers, bridging cultures through analysis, and finding patterns that matter.
My interdisciplinary background in German and Mathematics allows me to approach problems with both analytical rigor and cultural sensitivity, creating solutions that are not only technically sound but also meaningful across diverse contexts.
Featured Projects
Showcasing the intersection of data science, mathematics, and cultural understanding
Multilingual Sentiment Analysis
Cross-cultural sentiment analysis combining NLP with German linguistic patterns to understand emotional expression across languages.
Mathematical Modeling of Social Networks
Applied graph theory and statistical modeling to analyze social network dynamics in multilingual communities.
Cultural Data Visualization Platform
Interactive platform visualizing cultural trends through data, bridging quantitative analysis with qualitative insights.
About Me
A UC Berkeley rising senior combining data science rigor with interdisciplinary thinking
My Journey
As a triple major in Data Science, German, and Mathematics at UC Berkeley, I've discovered that the most compelling insights emerge at the intersection of disciplines.
My German studies have taught me to think critically about cultural context and communication, while mathematics provides the logical framework for understanding complex systems. Data science becomes the bridge that connects these worlds.
I believe the future of data science lies not just in technical proficiency, but in the ability to understand and communicate across cultural and disciplinary boundaries.
Data Science & ML
Python, R, TensorFlow, Scikit-learn, Statistical Modeling
Mathematics
Linear Algebra, Calculus, Statistics, Graph Theory, Optimization
German & Linguistics
Advanced German, Cultural Analysis, Cross-linguistic Research
Academic Excellence
UC Berkeley Rising Senior, Interdisciplinary Research
Let's Connect
I'm always interested in discussing data science, interdisciplinary research, or potential collaboration opportunities.